Digital hologram provides users with more detailed 3D information; However, its encoding distortion and the unique properties pose challenges to its quality assessment. A full reference hologram quality assessment method combining holographic plane and object plane is proposed. Firstly, the degradation degree of compressed hologram is measured using information fidelity criteria on the holographic plane. Secondly, significance weighted gradient similarity is extracted from the reconstructed multi view reference hologram and compressed hologram on the object plane, and global feature changes are measured using Grünwald-Letnikov fractional derivatives; then the similarity between the reconstructed multi view reference hologram and compressed hologram is calculated based on these two features. Finally, the calculation results of the holographic plane and the similarity of the object plane are used as joint features, and random forest is used to train the above features to establish a quality assessment model. The experimental results show that the Pearson linear correlation coefficient is about 0.917 9 and the Spearman rank correlation coefficient is about 0.907 5, which outperforms the relevant representative hologram quality assessment methods and has a higher degree of fit with the subjective perception of the human eye.